Poisson regression modeling of diarrhea events in pasuruan regency with maximum likelihood estimates and generalized method moment

Bambang Otok*, Dhian Rachmawati, Purhadi, Santi Purnami, Mahpolah Mahpolah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Context: Diarrhea characterized by a frequency increased of defecation more than 3 times/day accompanied by changes in consistency (becoming liquid). The causes of diarrhea can be divided into 2 parts, which are direct causes and indirect causes that can facilitate or accelerate the occurrence of diarrhea, including bacteria, nutritional conditions, hygiene and sanitation, social culture such as population density, economic status, low birth weight, and immunization. Aims: The purpose of this study to examine the factors that influence the incidence of diarrhea. Methods: This research used secondary data, the prevalence of diarrhea and risk factors in Pasuruan Regency Health Center. Poisson regression approach with maximum likelihood estimator (MLE) estimation and Generalized Method Moment (GMM) used in this study. Results: The results showed that GMM estimation method in the Poisson regression model gave better performance in terms of significance parameters compared to the MLE method. Conclusions: Factors affecting the increase of diarrhea occurrences in area with an estimated MLE Percentage of non-exclusive breastfeeding and Percentage of normal nutritional status. Whereas the GMM estimation is the percentage of non-exclusive breastfeeding, the percentage of low birth weight, the percentage of population density, the percentage of smokers among family members in the house, the percentage of incomplete immunizations, the percentage of under-five years old children less than 2, the percentage of normal nutritional status, and the percentage of middle class socioeconomic status.

Original languageEnglish
Article number103
JournalInternational Journal of Preventive Medicine
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Jan 2021

Keywords

  • Diarrhea
  • likelihood functions
  • regression analysis

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